Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 245 670 6 184 174 981 132 894 751 348 740 948 661 48 49 90 596 949 570 800
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 174 348 132 48 NA 948 49 245 740 NA 90 596 894 800 184 NA 661 751 6 981 949 570 670
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 1 3 5 1 3 3 5 4 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "t" "n" "f" "y" "j" "K" "Y" "Z" "P" "A"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 6 12 18
which( manyNumbersWithNA > 900 )
[1] 6 20 21
which( is.na( manyNumbersWithNA ) )
[1] 5 10 16
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 981 948 949
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 981 948 949
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 981 948 949
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "K" "Y" "Z" "P" "A"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "t" "n" "f" "y" "j"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE
[19] TRUE FALSE
which( manyNumbers %in% 300:600 )
[1] 10 17 19
sum( manyNumbers %in% 300:600 )
[1] 3
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "small" "small" NA "large" "small" "small" "large" NA "small" "large" "large" "large"
[15] "small" NA "large" "large" "small" "large" "large" "large" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "small" "small" "UNKNOWN" "large" "small" "small" "large" "UNKNOWN" "small"
[12] "large" "large" "large" "small" "UNKNOWN" "large" "large" "small" "large" "large" "large"
[23] "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 0 0 NA 948 0 0 740 NA 0 596 894 800 0 NA 661 751 0 981 949 570 670
unique( duplicatedNumbers )
[1] 2 1 3 5 4
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 1 3 5 4
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE TRUE
which.max( manyNumbersWithNA )
[1] 20
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 981
which.min( manyNumbersWithNA )
[1] 19
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 6
range( manyNumbersWithNA, na.rm = TRUE )
[1] 6 981
manyNumbersWithNA
[1] 174 348 132 48 NA 948 49 245 740 NA 90 596 894 800 184 NA 661 751 6 981 949 570 670
sort( manyNumbersWithNA )
[1] 6 48 49 90 132 174 184 245 348 570 596 661 670 740 751 800 894 948 949 981
sort( manyNumbersWithNA, na.last = TRUE )
[1] 6 48 49 90 132 174 184 245 348 570 596 661 670 740 751 800 894 948 949 981 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 981 949 948 894 800 751 740 670 661 596 570 348 245 184 174 132 90 49 48 6 NA NA NA
manyNumbersWithNA[1:5]
[1] 174 348 132 48 NA
order( manyNumbersWithNA[1:5] )
[1] 4 3 1 2 5
rank( manyNumbersWithNA[1:5] )
[1] 3 4 2 1 5
sort( mixedLetters )
[1] "A" "f" "j" "K" "n" "P" "t" "y" "Y" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 5 9 9 9 5 2 5 5 1 5
rank( manyDuplicates, ties.method = "min" )
[1] 3 8 8 8 3 2 3 3 1 3
rank( manyDuplicates, ties.method = "random" )
[1] 7 8 9 10 6 2 5 4 1 3
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 0.15021807 0.27517033 0.83855149 -0.15026076
[10] 0.93050383 -0.08539683 0.24923108 -0.53823340 0.01422160 0.26408372
round( v, 0 )
[1] -1 0 0 0 1 0 0 1 0 1 0 0 -1 0 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.2 0.3 0.8 -0.2 0.9 -0.1 0.2 -0.5 0.0 0.3
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.15 0.28 0.84 -0.15 0.93 -0.09 0.25 -0.54 0.01 0.26
floor( v )
[1] -1 -1 0 0 1 0 0 0 -1 0 -1 0 -1 0 0
ceiling( v )
[1] -1 0 0 1 1 1 1 1 0 1 0 1 0 1 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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